DIP/docs/embedding/VECTOR_SYNC_HTTP_PROVIDER.md

Vector-sync HTTP embedding provider

This provider supports two endpoints:

• POST {baseUrl}/vector-sync for single-text requests
• POST {baseUrl}/vectorize-batch for batch document requests

Single request

Request body:

{
  "model": "intfloat/multilingual-e5-large",
  "text": "This is a sample text to vectorize"
}

Batch request

Request body:

{
  "model": "intfloat/multilingual-e5-large",
  "truncate_text": false,
  "truncate_length": 512,
  "chunk_size": 20,
  "items": [
    {
      "id": "2f48fd5c-9d39-4d80-9225-ea0c59c77c9a",
      "text": "This is a sample text to vectorize"
    }
  ]
}

Provider configuration

batch-request:
  truncate-text: false
  truncate-length: 512
  chunk-size: 20

These values are used for /vectorize-batch calls and can also be overridden per request via EmbeddingRequest.providerOptions().

Orchestrator batch processing

To let RepresentationEmbeddingOrchestrator send multiple representations in one provider call, enable batch processing for jobs and for the model:

dip:
  embedding:
    jobs:
      enabled: true
      parallel-batch-count: 1
      process-in-batches: true
      execution-batch-size: 20

    models:
      e5-default:
        supports-batch: true

Notes:

• jobs are grouped by modelKey
• non-batch-capable models still fall back to single-item execution
• parallel-batch-count controls how many claimed job batches may be started in parallel
• execution-batch-size controls how many texts are sent in one /vectorize-batch request inside each claimed job batch